{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "64c24af2",
   "metadata": {},
   "source": [
    "# My realization GMT_trend2d vs library based robust_trend2d\n",
    "\n",
    "See pygmtsar.PRM class for my realization of GMT compatible robust trend estimator named before GMT_trend2d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6e6eb96f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib.lines import Line2D\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7218caeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "def GMT_trend2d(data, rank):\n",
    "    import numpy as np\n",
    "    from sklearn.linear_model import LinearRegression\n",
    "    # scale factor for normally distributed data is 1.4826\n",
    "    # https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.median_abs_deviation.html\n",
    "    MAD_NORMALIZE = 1.4826\n",
    "    # significance value\n",
    "    sig_threshold = 0.51\n",
    "\n",
    "    if rank not in [1,2,3]:\n",
    "        raise Exception('Number of model parameters \"rank\" should be 1, 2, or 3')\n",
    "\n",
    "    #see gmt_stat.c\n",
    "    def gmtstat_f_q (chisq1, nu1, chisq2, nu2):\n",
    "        import scipy.special as sc\n",
    "\n",
    "        if chisq1 == 0.0:\n",
    "            return 1\n",
    "        if chisq2 == 0.0:\n",
    "            return 0\n",
    "        return sc.betainc(0.5*nu2, 0.5*nu1, chisq2/(chisq2+chisq1))\n",
    "\n",
    "    if rank in [2,3]:\n",
    "        x = data[:,0]\n",
    "        x = np.interp(x, (x.min(), x.max()), (-1, +1))\n",
    "    if rank == 3:\n",
    "        y = data[:,1]\n",
    "        y = np.interp(y, (y.min(), y.max()), (-1, +1))\n",
    "    z = data[:,2]\n",
    "    w = np.ones(z.shape)\n",
    "\n",
    "    if rank == 1:\n",
    "        xy = np.expand_dims(np.zeros(z.shape),1)\n",
    "    elif rank == 2:\n",
    "        xy = np.expand_dims(x,1)\n",
    "    elif rank == 3:\n",
    "        xy = np.stack([x,y]).transpose()\n",
    "\n",
    "    # create linear regression object\n",
    "    mlr = LinearRegression()\n",
    "\n",
    "    chisqs = []\n",
    "    coeffs = []\n",
    "    while True:\n",
    "        # fit linear regression\n",
    "        mlr.fit(xy, z, sample_weight=w)\n",
    "\n",
    "        r = np.abs(z - mlr.predict(xy))\n",
    "        chisq = np.sum((r**2*w))/(z.size-3)    \n",
    "        chisqs.append(chisq)\n",
    "        k = 1.5 * MAD_NORMALIZE * np.median(r)\n",
    "        w = np.where(r <= k, 1, (2*k/r) - (k * k/(r**2)))\n",
    "        sig = 1 if len(chisqs)==1 else gmtstat_f_q(chisqs[-1], z.size-3, chisqs[-2], z.size-3)\n",
    "        # Go back to previous model only if previous chisq < current chisq\n",
    "        if len(chisqs)==1 or chisqs[-2] > chisqs[-1]:\n",
    "            coeffs = [mlr.intercept_, *mlr.coef_]\n",
    "\n",
    "        #print ('chisq', chisq, 'significant', sig)\n",
    "        if sig < sig_threshold:\n",
    "            break\n",
    "\n",
    "    # get the slope and intercept of the line best fit\n",
    "    return (coeffs[:rank])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "95ced63f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import statsmodels.api as sm\n",
    "\n",
    "def robust_trend2d(data, rank):\n",
    "    if rank not in [1, 2, 3]:\n",
    "        raise Exception('Number of model parameters \"rank\" should be 1, 2, or 3')\n",
    "\n",
    "    if rank in [2, 3]:\n",
    "        x = data[:, 0]\n",
    "        x = np.interp(x, (x.min(), x.max()), (-1, +1))\n",
    "    if rank == 3:\n",
    "        y = data[:, 1]\n",
    "        y = np.interp(y, (y.min(), y.max()), (-1, +1))\n",
    "    z = data[:, 2]\n",
    "\n",
    "    if rank == 1:\n",
    "        X = sm.add_constant(np.ones(z.shape))\n",
    "    elif rank == 2:\n",
    "        X = sm.add_constant(x)\n",
    "    elif rank == 3:\n",
    "        X = sm.add_constant(np.column_stack((x, y)))\n",
    "\n",
    "    rlm_model = sm.RLM(z, X)\n",
    "    rlm_results = rlm_model.fit()\n",
    "\n",
    "    return rlm_results.params[:rank]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "101ce344",
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_data(rank, num_points, noise_level):\n",
    "    np.random.seed(42)\n",
    "    x = np.linspace(-10, 10, num_points)\n",
    "    y = np.linspace(-10, 10, num_points)\n",
    "    if rank == 1:\n",
    "        z = 3 * x + 5 + noise_level * np.random.randn(num_points)\n",
    "        data = np.column_stack((x, y, z))\n",
    "    elif rank == 2:\n",
    "        z = 2 * x + 3 * y + 5 + noise_level * np.random.randn(num_points)\n",
    "        data = np.column_stack((x, y, z))\n",
    "    elif rank == 3:\n",
    "        z = 2 * x**2 + 3 * y**2 + 5 + noise_level * np.random.randn(num_points)\n",
    "        data = np.column_stack((x, y, z))\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "e9230da6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = generate_data(3, 100, 0)\n",
    "coefficients = robust_trend2d(data, 3)\n",
    "\n",
    "x = data[:, 0]\n",
    "y = data[:, 1]\n",
    "X, Y = np.meshgrid(x, y)\n",
    "Z = coefficients[0] + coefficients[1] * (X**2) + coefficients[2] * (Y**2)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "data_points = ax.scatter(data[:, 0], data[:, 1], data[:, 2], label=\"Data points\")\n",
    "surface = ax.plot_surface(X, Y, Z, alpha=0.5, color='r')\n",
    "\n",
    "ax.set_xlabel(\"X\")\n",
    "ax.set_ylabel(\"Y\")\n",
    "ax.set_zlabel(\"Z\")\n",
    "ax.set_title(\"3D Plot of generate_data(3, 100, 0) with Trend Surface\")\n",
    "\n",
    "# Create a custom proxy artist for the legend entry\n",
    "surface_proxy = Line2D([0], [0], linestyle='none', mfc='red', alpha=0.5, mec='none', marker='o', markersize=10)\n",
    "ax.legend([data_points, surface_proxy], ['Data points', 'Trend surface'], loc='upper left')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f5c89a4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = generate_data(3, 100, 50)\n",
    "coefficients = robust_trend2d(data, 3)\n",
    "\n",
    "x = data[:, 0]\n",
    "y = data[:, 1]\n",
    "X, Y = np.meshgrid(x, y)\n",
    "Z = coefficients[0] + coefficients[1] * (X**2) + coefficients[2] * (Y**2)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "data_points = ax.scatter(data[:, 0], data[:, 1], data[:, 2], label=\"Data points\")\n",
    "surface = ax.plot_surface(X, Y, Z, alpha=0.5, color='r')\n",
    "\n",
    "ax.set_xlabel(\"X\")\n",
    "ax.set_ylabel(\"Y\")\n",
    "ax.set_zlabel(\"Z\")\n",
    "ax.set_title(\"3D Plot of generate_data(3, 100, 50) with Trend Surface\")\n",
    "\n",
    "# Create a custom proxy artist for the legend entry\n",
    "surface_proxy = Line2D([0], [0], linestyle='none', mfc='red', alpha=0.5, mec='none', marker='o', markersize=10)\n",
    "ax.legend([data_points, surface_proxy], ['Data points', 'Trend surface'], loc='upper left')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a8c28f76",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, MSE    robust_trend2d, MSE  Winner               %\n",
      "------  -------------  ------------------  ---------------------  --------------  ------\n",
      "     1              0                 300                    300  robust_trend2d  100\n",
      "     1              1                 301                    301  robust_trend2d  100\n",
      "     1             10                 400                    400  robust_trend2d  100\n",
      "     1             50                2805                   2805  robust_trend2d  100\n",
      "     2              0               67501                  67501  robust_trend2d  100\n",
      "     2              1               67502                  67502  robust_trend2d  100\n",
      "     2             10               67594                  67596  GMT_trend2d     100\n",
      "     2             50               69969                  69978  GMT_trend2d      99.99\n",
      "     3              0               22335                  22248  robust_trend2d   99.61\n",
      "     3              1               22356                  22238  robust_trend2d   99.47\n",
      "     3             10               22377                  22331  robust_trend2d   99.79\n",
      "     3             50               24869                  24967  GMT_trend2d      99.61\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "from tabulate import tabulate\n",
    "\n",
    "def calculate_mse(data, coeffs, rank):\n",
    "    x = data[:, 0]\n",
    "    y = data[:, 1]\n",
    "    z_actual = data[:, 2]\n",
    "\n",
    "    if rank == 1:\n",
    "        z_predicted = coeffs[0]\n",
    "    elif rank == 2:\n",
    "        z_predicted = coeffs[0] + coeffs[1] * x\n",
    "    elif rank == 3:\n",
    "        z_predicted = coeffs[0] + coeffs[1] * x + coeffs[2] * y\n",
    "\n",
    "    mse = np.mean((z_actual - z_predicted) ** 2)\n",
    "    return mse\n",
    "\n",
    "\n",
    "def test_mse(num_points = 100*1000, ranks = [1, 2, 3], noise_levels = [0, 1, 10, 50]):\n",
    "    import warnings\n",
    "\n",
    "    results = []\n",
    "    # Suppress the specific warning\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "        for rank in ranks:\n",
    "            for noise_level in noise_levels:\n",
    "                data = generate_data(rank, num_points, noise_level)\n",
    "                # round the output\n",
    "                coeffs_gmt = [v.round(8) for v in GMT_trend2d(data, rank)]\n",
    "                coeffs_robust = robust_trend2d(data, rank)\n",
    "\n",
    "                mse_gmt = np.round(calculate_mse(data, coeffs_gmt, rank), 0)\n",
    "                mse_robust = np.round(calculate_mse(data, coeffs_robust, rank), 0)\n",
    "\n",
    "                winner = \"GMT_trend2d\" if mse_gmt < mse_robust else \"robust_trend2d\"\n",
    "\n",
    "                diff = np.round(100*(mse_gmt/mse_robust if mse_gmt < mse_robust else mse_robust/mse_gmt), 2)\n",
    "\n",
    "                results.append([rank, noise_level, mse_gmt, mse_robust, winner, diff])\n",
    "\n",
    "    headers = [\"Rank\", \"Noise Level\", \"GMT_trend2d, MSE\", \"robust_trend2d, MSE\", \"Winner\", \"%\"]\n",
    "    print(tabulate(results, headers=headers))\n",
    "\n",
    "test_mse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b9ff759a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, [ms]    robust_trend2d, [ms]  Winner         %\n",
      "------  -------------  -------------------  ----------------------  -----------  ---\n",
      "     1              0                   14                     139  GMT_trend2d   10\n",
      "     1              1                    8                     158  GMT_trend2d    5\n",
      "     1             10                   14                     302  GMT_trend2d    5\n",
      "     1             50                   15                     282  GMT_trend2d    5\n",
      "     2              0                    8                    1001  GMT_trend2d    1\n",
      "     2              1                   13                     301  GMT_trend2d    4\n",
      "     2             10                   13                     270  GMT_trend2d    5\n",
      "     2             50                   13                     224  GMT_trend2d    6\n",
      "     3              0                   45                    1185  GMT_trend2d    4\n",
      "     3              1                   36                    1154  GMT_trend2d    3\n",
      "     3             10                   43                    1262  GMT_trend2d    3\n",
      "     3             50                   51                    1153  GMT_trend2d    4\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import time\n",
    "from tabulate import tabulate\n",
    "\n",
    "def measure_time(func, data, rank, n_runs):\n",
    "    start_time = time.perf_counter()\n",
    "    _ = [func(data, rank) for i in range(n_runs)]\n",
    "    end_time = time.perf_counter()\n",
    "    return (end_time - start_time)/n_runs\n",
    "\n",
    "# aligning uses 50...100 ksamples for a few subswaths\n",
    "def test_time(num_points = 100*1000, n_runs = 50, ranks = [1, 2, 3], noise_levels = [0, 1, 10, 50]):\n",
    "    import warnings\n",
    "    \n",
    "    results = []\n",
    "    # Suppress the specific warning\n",
    "    with warnings.catch_warnings():\n",
    "        warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
    "        for rank in ranks:\n",
    "            for noise_level in noise_levels:\n",
    "                data = generate_data(rank, num_points, noise_level)\n",
    "\n",
    "                gmt_time = np.round(1000*measure_time(GMT_trend2d, data, rank, n_runs), 0)\n",
    "                robust_time = np.round(1000*measure_time(robust_trend2d, data, rank, n_runs), 0)\n",
    "\n",
    "                winner = \"GMT_trend2d\" if gmt_time < robust_time else \"robust_trend2d\"\n",
    "\n",
    "                diff = np.round(100*(gmt_time/robust_time if gmt_time < robust_time else robust_time/gmt_time), 0)\n",
    "\n",
    "                results.append([rank, noise_level, gmt_time, robust_time, winner, diff])\n",
    "\n",
    "    headers = [\"Rank\", \"Noise Level\", \"GMT_trend2d, [ms]\", \"robust_trend2d, [ms]\", \"Winner\", \"%\"]\n",
    "    print(tabulate(results, headers=headers))\n",
    "\n",
    "test_time()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7bb1824d",
   "metadata": {},
   "source": [
    "## Some Improvements #1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "70636b2d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import statsmodels.api as sm\n",
    "\n",
    "def robust_trend2d(data, rank):\n",
    "    if rank not in [1, 2, 3]:\n",
    "        raise Exception('Number of model parameters \"rank\" should be 1, 2, or 3')\n",
    "\n",
    "    if rank in [2, 3]:\n",
    "        x = data[:, 0]\n",
    "        x = np.interp(x, (x.min(), x.max()), (-1, +1))\n",
    "    if rank == 3:\n",
    "        y = data[:, 1]\n",
    "        y = np.interp(y, (y.min(), y.max()), (-1, +1))\n",
    "    z = data[:, 2]\n",
    "\n",
    "    if rank == 1:\n",
    "        X = sm.add_constant(np.ones(z.shape))\n",
    "    elif rank == 2:\n",
    "        X = sm.add_constant(x)\n",
    "    elif rank == 3:\n",
    "        X = sm.add_constant(np.column_stack((x, y)))\n",
    "\n",
    "    # Iterate only once for the RLM model\n",
    "    rlm_model = sm.RLM(z, X, M=sm.robust.norms.HuberT(), hasconst=True)\n",
    "    rlm_results = rlm_model.fit(update_scale=False, maxiter=1)\n",
    "\n",
    "    return rlm_results.params[:rank]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f1ba43cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, MSE    robust_trend2d, MSE  Winner               %\n",
      "------  -------------  ------------------  ---------------------  --------------  ------\n",
      "     1              0                 300                    300  robust_trend2d  100\n",
      "     1              1                 301                    301  robust_trend2d  100\n",
      "     1             10                 400                    400  robust_trend2d  100\n",
      "     1             50                2805                   2805  robust_trend2d  100\n",
      "     2              0               67501                  67501  robust_trend2d  100\n",
      "     2              1               67502                  67502  robust_trend2d  100\n",
      "     2             10               67594                  67598  GMT_trend2d      99.99\n",
      "     2             50               69969                  69989  GMT_trend2d      99.97\n",
      "     3              0               22335                  22231  robust_trend2d   99.53\n",
      "     3              1               22356                  22553  GMT_trend2d      99.13\n",
      "     3             10               22377                  22333  robust_trend2d   99.8\n",
      "     3             50               24869                  25014  GMT_trend2d      99.42\n"
     ]
    }
   ],
   "source": [
    "test_mse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "974c06c1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, [ms]    robust_trend2d, [ms]  Winner         %\n",
      "------  -------------  -------------------  ----------------------  -----------  ---\n",
      "     1              0                    7                      38  GMT_trend2d   18\n",
      "     1              1                    7                      28  GMT_trend2d   25\n",
      "     1             10                   10                      32  GMT_trend2d   31\n",
      "     1             50                   13                      32  GMT_trend2d   41\n",
      "     2              0                    8                      63  GMT_trend2d   13\n",
      "     2              1                   13                      59  GMT_trend2d   22\n",
      "     2             10                   13                      57  GMT_trend2d   23\n",
      "     2             50                   12                      66  GMT_trend2d   18\n",
      "     3              0                   43                      80  GMT_trend2d   54\n",
      "     3              1                   38                      84  GMT_trend2d   45\n",
      "     3             10                   42                      80  GMT_trend2d   52\n",
      "     3             50                   52                      76  GMT_trend2d   68\n"
     ]
    }
   ],
   "source": [
    "test_time()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b14bda1",
   "metadata": {},
   "source": [
    "## Some Improvements #2\n",
    "\n",
    "By default, sm.RLM uses the Huber's t weighting function. There are some other weighting functions such as Tukey's biweight or the Hampel weighting function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c39f23d9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def robust_trend2d(data, rank):\n",
    "    if rank not in [1, 2, 3]:\n",
    "        raise Exception('Number of model parameters \"rank\" should be 1, 2, or 3')\n",
    "\n",
    "    if rank in [2, 3]:\n",
    "        x = data[:, 0]\n",
    "        x = np.interp(x, (x.min(), x.max()), (-1, +1))\n",
    "    if rank == 3:\n",
    "        y = data[:, 1]\n",
    "        y = np.interp(y, (y.min(), y.max()), (-1, +1))\n",
    "    z = data[:, 2]\n",
    "\n",
    "    if rank == 1:\n",
    "        X = sm.add_constant(np.ones(z.shape))\n",
    "    elif rank == 2:\n",
    "        X = sm.add_constant(x)\n",
    "    elif rank == 3:\n",
    "        X = sm.add_constant(np.column_stack((x, y)))\n",
    "\n",
    "    rlm_model = sm.RLM(z, X, M=sm.robust.norms.Hampel())\n",
    "    rlm_results = rlm_model.fit()\n",
    "\n",
    "    return rlm_results.params[:rank]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2178d018",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, MSE    robust_trend2d, MSE  Winner               %\n",
      "------  -------------  ------------------  ---------------------  --------------  ------\n",
      "     1              0                 300                    300  robust_trend2d  100\n",
      "     1              1                 301                    301  robust_trend2d  100\n",
      "     1             10                 400                    400  robust_trend2d  100\n",
      "     1             50                2805                   2805  robust_trend2d  100\n",
      "     2              0               67501                  67501  robust_trend2d  100\n",
      "     2              1               67502                  67501  robust_trend2d  100\n",
      "     2             10               67594                  67587  robust_trend2d   99.99\n",
      "     2             50               69969                  69931  robust_trend2d   99.95\n",
      "     3              0               22335                  22220  robust_trend2d   99.49\n",
      "     3              1               22356                  22316  robust_trend2d   99.82\n",
      "     3             10               22377                  22430  GMT_trend2d      99.76\n",
      "     3             50               24869                  24841  robust_trend2d   99.89\n"
     ]
    }
   ],
   "source": [
    "test_mse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "b5cc15e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  Rank    Noise Level    GMT_trend2d, [ms]    robust_trend2d, [ms]  Winner         %\n",
      "------  -------------  -------------------  ----------------------  -----------  ---\n",
      "     1              0                    7                      35  GMT_trend2d   20\n",
      "     1              1                    6                      38  GMT_trend2d   16\n",
      "     1             10                   14                      79  GMT_trend2d   18\n",
      "     1             50                   10                     108  GMT_trend2d    9\n",
      "     2              0                   10                      71  GMT_trend2d   14\n",
      "     2              1                   13                     229  GMT_trend2d    6\n",
      "     2             10                   15                     215  GMT_trend2d    7\n",
      "     2             50                   12                     190  GMT_trend2d    6\n",
      "     3              0                   54                      95  GMT_trend2d   57\n",
      "     3              1                   42                      94  GMT_trend2d   45\n",
      "     3             10                   41                      90  GMT_trend2d   46\n",
      "     3             50                   51                    1224  GMT_trend2d    4\n"
     ]
    }
   ],
   "source": [
    "test_time()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03445e81",
   "metadata": {},
   "source": [
    "## Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "29c7ce32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([174.83558692846418, 0.03710470618011453, 0.037104706180114515],\n",
       " array([1.74929824e+02, 3.44831683e-02, 3.44831683e-02]))"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GMT_trend2d(generate_data(3,100, 1), 3), robust_trend2d(generate_data(3,100, 1), 3)"
   ]
  }
 ],
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